1. Field of the Invention
The present invention relates generally to Doppler-frequency tracking, and more particularly, to the tracking of frequency shift due to the Doppler effect in mobile communications systems.
2. Description of the Related Art
Communication systems operating in the mobile environment are subject to a continuously changing channel. The rate of change of the channel depends primarily on the relative velocities of the transmitter, receiver, and reflective objects in the environment. When the channel changes over time, the signal bandwidth is increased by the Doppler frequency, or Doppler bandwidth.
Consequently, optimizing receiver performance involves knowledge or estimation of various parameters, e.g., received signal phase, amplitude, and noise level, which depend on the channel as the channel changes over time. Various techniques for estimating such parameters are known in the art, many of which employ filtering in order to remove out-of-band noise from the estimation data. The filter bandwidth is typically set to reject energy at frequencies greater than the Doppler frequency while retaining all energy within the Doppler bandwidth, to prevent the loss of useful information. Thus, the Doppler frequency is tracked as it changes over time, so that relevant filter parameters may be updated accordingly.
One traditional approach to Doppler-frequency estimation involves the use of covariance methods, which utilize measured estimates of the channel state, along with various assumptions about the statistics of the channel process to derive estimators of Doppler frequency. Another approach involves the use of level-crossing rate methods, which use channel state measurements to determine the rate at which the channel level crosses a given envelope power level. The crossing rate is then used along with estimators, again derived using assumptions on the channel process, to estimate the Doppler frequency.
The foregoing approaches to Doppler-frequency estimation tend to be computationally complex and difficult to implement, often using transcendental functions that may be unsuitable for hardware. These approaches also tend to lead to relatively inaccurate estimates, resulting in poor receiver performance, particularly at low signal-to-noise ratios. Moreover, these methods are designed to work in channels having specific statistical properties, which may be over-simplified and poor models of real-world channels.